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Closed-Loop Control of Extrusion-Based Bioprinting Through Real-Time Computer Vision

Arduengo Javier, Hascoët Nicolas, Chinesta Francisco, Hascoet Jean-Yves

Journal of Machine Engineering

2025

Vol. 25, No. 2

28--42

Bioprinting is the technology that combines the use of living matter and biomaterials to manufacture biological models, tissues, and structures layer by layer for applications in regenerative medicine, drug testing, and tissue engineering. Among bioprinting techniques, extrusion-based methods are the most widely used because of their relative simplicity, affordability, and ability to handle as wide range of biomaterials, including those with high viscosities. However, achieving consistent print quality remains a challenge, as the rheological properties of bioinks are highly variable and sensitive to environmental factors such as temperature. A critical aspect of print quality is maintaining a consistent and predictable line width, as pre-programmed trajectories and design fidelity rely on this parameter being well controlled. This work introduces a closed-loop control system for Extrusion-Based Bioprinting (EBB), utilizing real-time computer vision. The system employs a camera that is placed to monitor the line width immediately after extrusion, enabling real-time feedback to adjust the feedrate of the extrusion mechanism. This approach ensures consistent line widths across a wide range of materials and conditions, addressing the variability that traditionally hampers EBB. The method was validated using a Pluronic hydrogel, achieving closed-loop control over a wide range of target line widths. These findings demonstrate the potential for automated, robust bioprinting with improved reproducibility and precision, advancing the reliability of this technology for biomedical applications.

Open-loop control system for high precision extrusion-based bioprinting through machine learning modelling

Arduengo Javier, Hascoet Nicolas, Chinesta Francisco, Hascoet Jean-Yves

Journal of Machine Engineering

2024

Vol. 24, No. 1

103--117

Bioprinting is a process that uses 3D printing techniques to combine cells, growth factors, and biomaterials to create biomedical components, often with the aim of imitating natural tissue characteristics. Typically, 3D bioprinting adopts a layer-by-layer method, using materials known as bio-inks to build structures resembling tissues. This study introduces an open-loop control system designed to improve the accuracy of extrusion-based bioprinting techniques, which is composed of a specific experimental setup and a series of algorithms and models. Firstly, a method employing Logistic Regression is used to select the tests that will serve to train and test the following model. Then, using a Machine Learning Algorithm, a model that allows the optimization of printing parameters and enables process control through an open-loop system was developed. Through rigorous experimentation and validation, it is shown that the model exhibits a high degree of accuracy in independent tests. Thus, the control system offers predictability and adaptability capabilities to ensure the consistent production of high-quality bioprinted structures. Experimental results confirm the efficacy of this machine learning model and the open-loop control system in achieving optimal bioprinting outcomes.